feat: security overhaul (proxy ssrf fix, streaming sanitization, docker optimization)

_bmad/bmgd/gametest/knowledge/balance-testing.md

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+# Balance Testing for Games
+
+## Overview
+
+Balance testing validates that your game's systems create fair, engaging, and appropriately challenging experiences. It covers difficulty, economy, progression, and competitive balance.
+
+## Types of Balance
+
+### Difficulty Balance
+
+- Is the game appropriately challenging?
+- Does difficulty progress smoothly?
+- Are difficulty spikes intentional?
+
+### Economy Balance
+
+- Is currency earned at the right rate?
+- Are prices fair for items/upgrades?
+- Can the economy be exploited?
+
+### Progression Balance
+
+- Does power growth feel satisfying?
+- Are unlocks paced well?
+- Is there meaningful choice in builds?
+
+### Competitive Balance
+
+- Are all options viable?
+- Is there a dominant strategy?
+- Do counters exist for strong options?
+
+## Balance Testing Methods
+
+### Spreadsheet Modeling
+
+Before implementation, model systems mathematically:
+
+- DPS calculations
+- Time-to-kill analysis
+- Economy simulations
+- Progression curves
+
+### Automated Simulation
+
+Run thousands of simulated games:
+
+- AI vs AI battles
+- Economy simulations
+- Progression modeling
+- Monte Carlo analysis
+
+### Telemetry Analysis
+
+Gather data from real players:
+
+- Win rates by character/weapon/strategy
+- Currency flow analysis
+- Completion rates by level
+- Time to reach milestones
+
+### Expert Testing
+
+High-skill players identify issues:
+
+- Exploits and degenerate strategies
+- Underpowered options
+- Skill ceiling concerns
+- Meta predictions
+
+## Key Balance Metrics
+
+### Combat Balance
+
+| Metric                    | Target              | Red Flag                  |
+| ------------------------- | ------------------- | ------------------------- |
+| Win rate (symmetric)      | 50%                 | <45% or >55%              |
+| Win rate (asymmetric)     | Varies by design    | Outliers by >10%          |
+| Time-to-kill              | Design dependent    | Too fast = no counterplay |
+| Damage dealt distribution | Even across options | One option dominates      |
+
+### Economy Balance
+
+| Metric               | Target               | Red Flag                        |
+| -------------------- | -------------------- | ------------------------------- |
+| Currency earned/hour | Design dependent     | Too fast = trivializes content  |
+| Item purchase rate   | Healthy distribution | Nothing bought = bad prices     |
+| Currency on hand     | Healthy churn        | Hoarding = nothing worth buying |
+| Premium currency     | Reasonable value     | Pay-to-win concerns             |
+
+### Progression Balance
+
+| Metric             | Target                 | Red Flag               |
+| ------------------ | ---------------------- | ---------------------- |
+| Time to max level  | Design dependent       | Too fast = no journey  |
+| Power growth curve | Smooth, satisfying     | Flat periods = boring  |
+| Build diversity    | Multiple viable builds | One "best" build       |
+| Content completion | Healthy progression    | Walls or trivial skips |
+
+## Balance Testing Process
+
+### 1. Define Design Intent
+
+- What experience are you creating?
+- What should feel powerful?
+- What trade-offs should exist?
+
+### 2. Model Before Building
+
+- Spreadsheet the math
+- Simulate outcomes
+- Identify potential issues
+
+### 3. Test Incrementally
+
+- Test each system in isolation
+- Then test systems together
+- Then test at scale
+
+### 4. Gather Data
+
+- Internal playtesting
+- Telemetry from beta
+- Expert feedback
+
+### 5. Iterate
+
+- Adjust based on data
+- Re-test changes
+- Document rationale
+
+## Common Balance Issues
+
+### Power Creep
+
+- **Symptom:** New content is always stronger
+- **Cause:** Fear of releasing weak content
+- **Fix:** Sidegrades over upgrades, periodic rebalancing
+
+### Dominant Strategy
+
+- **Symptom:** One approach beats all others
+- **Cause:** Insufficient counters, math oversight
+- **Fix:** Add counters, nerf dominant option, buff alternatives
+
+### Feast or Famine
+
+- **Symptom:** Players either crush or get crushed
+- **Cause:** Snowball mechanics, high variance
+- **Fix:** Comeback mechanics, reduce variance
+
+### Analysis Paralysis
+
+- **Symptom:** Too many options, players can't choose
+- **Cause:** Over-complicated systems
+- **Fix:** Simplify, provide recommendations
+
+## Balance Tools
+
+### Spreadsheets
+
+- Model DPS, TTK, economy
+- Simulate progression
+- Compare options side-by-side
+
+### Simulation Frameworks
+
+- Monte Carlo for variance
+- AI bots for combat testing
+- Economy simulations
+
+### Telemetry Systems
+
+- Track player choices
+- Measure outcomes
+- A/B test changes
+
+### Visualization
+
+- Graphs of win rates over time
+- Heat maps of player deaths
+- Flow charts of progression
+
+## Balance Testing Checklist
+
+### Pre-Launch
+
+- [ ] Core systems modeled in spreadsheets
+- [ ] Internal playtesting complete
+- [ ] No obvious dominant strategies
+- [ ] Difficulty curve feels right
+- [ ] Economy tested for exploits
+- [ ] Progression pacing validated
+
+### Live Service
+
+- [ ] Telemetry tracking key metrics
+- [ ] Regular balance reviews scheduled
+- [ ] Player feedback channels monitored
+- [ ] Hotfix process for critical issues
+- [ ] Communication plan for changes
+
+## Communicating Balance Changes
+
+### Patch Notes Best Practices
+
+- Explain the "why" not just the "what"
+- Use concrete numbers when possible
+- Acknowledge player concerns
+- Set expectations for future changes
+
+### Example
+
+```
+**Sword of Valor - Damage reduced from 100 to 85**
+Win rate for Sword users was 58%, indicating it was
+overperforming. This brings it in line with other weapons
+while maintaining its identity as a high-damage option.
+We'll continue monitoring and adjust if needed.
+```